Optimising topical query decomposition

Marcin Sydow, Francesco Bonchi, Carlos Castillo, Debora Donato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Topical query decomposition (TQD) is a paradigm recently in [1], which, given a query, returns to the user a of queries that cover the answer set of the original query. TQD problem was studied as a variant of the set-cover and solved by means of a greedy algorithm. paper aims to strengthen the original formulation introducing a new global objective function, and thus the problem as a combinatorial optimisation one. a reformulation defines a common framework allowing formal evaluation and comparison of different approaches TQD.We apply simulated annealing, a sub-optimal metaheuristic, the problem of topical query decomposition and show, through a large experimentation on a data sample from an actual query log, that such meta-heuristic achieves better results than the greedy algorithm.

Original languageEnglish
Title of host publicationProceedings of Workshop on Web Search Click Data, WSCD'09
Number of pages5
Publication statusPublished - 14 Jul 2009
EventWorkshop on Web Search Click Data, WSCD'09 - Barcelona, Spain
Duration: 9 Feb 20099 Feb 2009

Publication series

NameProceedings of Workshop on Web Search Click Data, WSCD'09


OtherWorkshop on Web Search Click Data, WSCD'09



  • Objective function
  • Query decomposition
  • Query logs
  • Query recommendation
  • Simulated annealing

ASJC Scopus subject areas

  • Information Systems
  • Software

Cite this

Sydow, M., Bonchi, F., Castillo, C., & Donato, D. (2009). Optimising topical query decomposition. In Proceedings of Workshop on Web Search Click Data, WSCD'09 (pp. 43-47). (Proceedings of Workshop on Web Search Click Data, WSCD'09). https://doi.org/10.1145/1507509.1507516